Structure and diffusion of ZnO–SrO–CaO–Na2O–SiO2 bioactive glasses: a combined high energy X-ray diffraction and molecular dynamics simulations study
Bibliographic record
Abstract
Novel bioactive glasses that can release ions such as strontium and zinc provide bone growth enhancement and antibacterial properties that earlier-generation bioglasses did not possess. These glasses find applications in bone cementation, restoration and in tissue engineering. In this paper, we present combined experimental and simulation studies to explain the structure and diffusion of ZnO–SrO–CaO–Na2O–SiO2 bioactive glasses with the aim of understanding the short and medium range structure of these glasses, the structural correlation to their dissolution behaviors, and their bioactivity. High energy X-ray diffraction experiments have been performed to obtain structural information and to validate the structure models from simulations. Three glass compositions with ZnO/Na2O substitutions have been studied using molecular dynamics simulations to characterize the glass structure and calculate the ionic diffusion in these glasses. The results provide insight to local environments and structural role of zinc ions, the medium range structural features such as Qn distribution, and ionic diffusion characteristics of these bioactive glasses. The structure and ionic diffusion results are discussed in correlation to the dissolution behaviors and the bioactivity of these glasses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".